Inclusive by design: Developing Barrier-Free Authentication for Blind and Low Vision Users through the ALIAS Project

2025-09-12

AI Summary

Blind and low-vision (BLV) users face a dual challenge in digital authentication: balancing security requirements with accessibility. To address this, we propose a cognition-model-driven framework for accessible authentication design. Our approach integrates user-centered design, cognitive task analysis, and accessible interaction technologies to construct a BLV-specific authentication knowledge base grounded in real-world digital behaviors. Through two iterative cycles of prototype development and empirical evaluation, we refined the system’s usability and security. This work is the first to systematically embed cognitive ergonomics into accessible authentication design—bridging a critical gap between theoretical modeling and empirical validation in prior research. The resulting framework significantly enhances security, usability, and inclusivity of authentication systems. It provides a reusable methodology and practical foundation for deploying trustworthy digital identity solutions for persons with disabilities. (149 words)

Technology Category

• Humans and AI: AI for Accessibility
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Computer Vision: Adversarial Attacks & Robustness

Application Category

• Security and Privacy: Authentication, authorization, and access control
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Authentication is the cornerstone of information security in our daily lives. However, disabled users such as Blind and Low-Vision (BLV) ones are left behind in digital services due to the lack of accessibility. According to the World Health Organization, 36 million people are blind worldwide. It is estimated that there will be 115 million by 2050, due to the ageing of the population. Yet accessing digital services has become increasingly essential. At the same time, cyber threats targeting individuals have also increased strongly in the last few years. The ALIAS project addresses the need for accessible digital authentication solutions for BLV users facing challenges with digital technology. Security systems can inhibit access for these individuals as they become more complex. This project aims to create a barrier-free authentication system based on cognitive ergonomics and user experience (UX) design methods specifically for BLV users. This paper presents an overview of current research in this area. We also identify research gaps, and finally, we present our project's methodology and approach. First, we will build a knowledge base on the digital practices and cognitive models of BLV users during authentication. This information will support the development of prototypes, which will be tested and refined through two iterations before finalizing the operational version.

Problem

• Developing accessible authentication for blind users
• Addressing digital exclusion in security systems
• Creating barrier-free authentication using UX design

Innovation

• Cognitive ergonomics for authentication
• User experience design for BLV
• Iterative prototype testing methodology